CASISD OpenIR研究单元&专题: 系统分析与管理研究所http://ir.casisd.cn:80/handle/190111/85092024-03-29T14:04:53Z2024-03-29T14:04:53ZNumerical study for solidification of water inside a storage tank considering copper oxide nanoparticlesWang, JianAlawee, Wissam H.Dhahad, Hayder A.Nofal, Taher A.Musa, AwadXu, Pinghttp://ir.casisd.cn:80/handle/190111/120752023-05-30T07:37:29Z2023-05-30T07:37:29Z题名: Numerical study for solidification of water inside a storage tank considering copper oxide nanoparticles
作者: Wang, Jian; Alawee, Wissam H.; Dhahad, Hayder A.; Nofal, Taher A.; Musa, Awad; Xu, Ping
摘要: In this study, for improving the rate of freezing nano-sized material with different diameter has been dispersed in to water. The geometry of tank has two cold surfaces with circular and wavy shapes and two insulated walls were applied. Also, two inclined fins were connected to circular surface which helps the expedition of freezing. Finite element approach based on Galerkin discretization was applied for solving the energy equation and concentration of solid PCM. The velocity equations were not involved in model because of low impact of gravity force. With start of process, ice front moves from two sides to middle regions. The solidification rate improves around 38.42% with adding nanoparticles. Augmenting the fraction of nano-powders makes the period to decline about 12.04%. With increase of size of powders at first needed time declines around 11.4% then it augments around 25.23%.2023-05-30T07:37:29ZTime-varying determinants of China's liquefied natural gas import price: A dynamic model averaging approachWang, TiantianQu, WanZhang, DayongJi, QiangWu, Feihttp://ir.casisd.cn:80/handle/190111/120732023-05-30T07:37:26Z2023-05-30T07:37:26Z题名: Time-varying determinants of China's liquefied natural gas import price: A dynamic model averaging approach
作者: Wang, Tiantian; Qu, Wan; Zhang, Dayong; Ji, Qiang; Wu, Fei
摘要: We adopt a dynamic model averaging (DMA) approach to study the time-varying impacts of several domestic and international factors on the volatility and premium of China's liquefied natural gas (LNG) import price from January 2008 to December 2020. China's LNG import price tends to be more affected by domestic market in-formation than by international crude oil prices. The demand side factors in the domestic market, including gas consumption, weather conditions and industrial growth, are shown to be the major drivers of the dynamics of China's LNG import price. Relative to the influences of the US or European gas markets, China's LNG import price is more sensitive to the impacts of its Japanese counterpart, which could be attributed to their similar pricing mechanisms. The high premium of China's LNG import price is also largely caused by increasing domestic energy demands. Our results further provide evidence of the benefits of marketizing the natural gas pricing in China. While trying to secure natural gas supply, more efforts should be made to keep promoting the liberali-sation and marketisation of the domestic natural gas market.2023-05-30T07:37:26ZA dynamic ensemble learning with multi-objective optimization for oil prices predictionHao, JunFeng, QianqianYuan, JiaxinSun, XiaoleiLi, Jianpinghttp://ir.casisd.cn:80/handle/190111/120672023-05-30T07:37:19Z2023-05-30T07:37:19Z题名: A dynamic ensemble learning with multi-objective optimization for oil prices prediction
作者: Hao, Jun; Feng, Qianqian; Yuan, Jiaxin; Sun, Xiaolei; Li, Jianping
摘要: Accurately predicting oil prices is a challenging task since its complex fluctuation characteristics. This paper innovatively introduces the metabolism mechanism and sliding window technology and proposes a dynamic time-varying weight ensemble prediction model with multi-objective programming to ameliorate the oil price's prediction performance. This paper first adopts the random forest to select and generate the best feature sets. Second, different individual models are selected to build a heterogeneous ensemble prediction framework. Then, a multi-objective weight generation model is established by considering horizontal and directional accuracy. Moreover, the nondominated sorting genetic algorithm-II is utilized to compute the prediction errors of a single model at different stages and achieve model optimization selection and ensemble weight generation. Finally, we take Brent and WTI oil prices as the prediction objects to verify the effectiveness and superiority of the proposed model. The experimental results reveal that the dynamic time-varying weight ensemble forecasting model has excellent prediction capability for oil prices and can become an effective forecasting tool.2023-05-30T07:37:19ZEnergy market reforms in China and the time-varying connectedness of domestic and international marketsWang, TiantianWu, FeiZhang, DayongJi, Qianghttp://ir.casisd.cn:80/handle/190111/120632023-05-30T07:37:14Z2023-05-30T07:37:14Z题名: Energy market reforms in China and the time-varying connectedness of domestic and international markets
作者: Wang, Tiantian; Wu, Fei; Zhang, Dayong; Ji, Qiang
摘要: China is the world's largest energy consumer and a considerable force in international energy markets. Continuous market reforms in the country together with the ongoing energy transition due to the commitment to carbon neutrality have brought fundamental changes to Chinese energy markets and have resulted in new sources of uncertainty in international energy markets. It is therefore important to investigate market linkages between China and the world from a dynamic perspective. This paper adopts the time-varying parameter VAR (TVP-VAR) model and the network spillover approach to explore the time-varying linkages between China and the international energy markets. The results show that the marketization process in China has led to significant changes in spillover patterns between international energy markets and Chinese domestic markets. Dynamics in the Chinese energy markets have played an increasingly important role in affecting international energy price movements. There is also clear evidence that the energy transition process in China has driven risk spillovers from the country to the international energy markets.2023-05-30T07:37:14ZEnvironmental regulations, clean energy access, and household energy poverty: Evidence from ChinaMa, RufeiDeng, LiqianJi, QiangZhai, Pengxianghttp://ir.casisd.cn:80/handle/190111/120592023-05-30T07:37:10Z2023-05-30T07:37:10Z题名: Environmental regulations, clean energy access, and household energy poverty: Evidence from China
作者: Ma, Rufei; Deng, Liqian; Ji, Qiang; Zhai, Pengxiang
摘要: This paper examines the effect of environmental regulations on energy poverty and analyses whether clean energy access, the access to modern energy services, is an important channel through which environmental regulations affect energy poverty in China. Using household-level survey data in China from 2012 to 2018, we find that enacting tightened environmental regulations leads to greater affordability problems for households using non-clean energy and deepens the degree of their energy poverty. Furthermore, we show that capable or sufficient access to clean energy enables households to obtain clean energy at a lower price, thus reducing the adverse effect of environmental regulations on household energy poverty. Our results have important implica-tions for environmental and energy policy makers.2023-05-30T07:37:10ZEnergy-food nexus scarcity risk and the synergic impact of climate policy: A global production network perspectiveXia, YanYan, Bingqianhttp://ir.casisd.cn:80/handle/190111/120572023-05-30T07:37:07Z2023-05-30T07:37:07Z题名: Energy-food nexus scarcity risk and the synergic impact of climate policy: A global production network perspective
作者: Xia, Yan; Yan, Bingqian
摘要: Carbon neutrality has been a global consensus to navigate away from catastrophic climate change. In particular, such climate changes also generate inevitable influences on economic securities, such as energy security and food security, through energy structure transformation etc. Energy and food are essential elements for human beings, and they are naturally linked to sustainable development. Usually, emergency events, such as the COVID-19 pandemic, may threaten energy security or food security in a region, the risk of which would be amplified due to the energy-food nexus effect. This is no doubt also a challenge and an opportunity for countries to achieve carbon neutrality. To realize the stable pathways to carbon neutrality, it is important to analyze the energy scarcity risk and food scarcity risk of each industry and country as well as the nexus effect between energy and food. In this paper, we combine multi-regional input-output (MRIO) analysis with network control analysis (NCA) to investigate the dependence degree of each country and region on energy and food resources as well as the risk transmission network of the energy-food scarcity nexus. Base on this, the impact of climate policy on energy-food nexus scarcity risk is analyzed. We found some interesting conclusions. First, regarding the risk transmission network of the energy-food scarcity nexus, China, Germany and the US are the main generators, and the main receptors are Taiwan, Mexico and the Netherlands. These results imply that international trade transfers energy/food scarcity to geographically distant regions via the international supply chain. Second, as for the scarcity risk per unit of output, small economies that rely heavily on imported energy or food (such as Cyprus and Luxemburg) have the highest scarcity risk and are among the top receptors of transmitted risks. We suggest collaborative conservation and management of energy and food resources. Third, the analyses that assess the emission intensity and scarcity risk find that implementation of emission control policies could significantly decrease initial energy scarcity risk and energy-food nexus scarcity risk. This implies that besides emission reduction achievement, climate policies bring co-benefits of energy-food nexus security. Moreover, the co-benefit of energy and food nexus security for low income economies associated with climate policy is much higher than that for high income economies.2023-05-30T07:37:07ZThe effect of social sphere digitalization on green total factor productivity in China: Evidence from a dynamic spatial Durbin modelGu, BingmeiLiu, JiaguoJi, Qianghttp://ir.casisd.cn:80/handle/190111/120562023-05-30T07:37:06Z2023-05-30T07:37:06Z题名: The effect of social sphere digitalization on green total factor productivity in China: Evidence from a dynamic spatial Durbin model
作者: Gu, Bingmei; Liu, Jiaguo; Ji, Qiang
摘要: Digitalization has been the new engine of development that drives the regional economy, but scant empirical studies investigate the linkage between the social sphere digitalization and green total factor productivity (GTFP). Based on the quantitative and comprehensive index of digitalization development, the study calculates the digital economy from the social sphere in China's 279 cities between 2011 and 2019. Besides, the impact of social sphere digitalization on GTFP is examined using the dynamic spatial Durbin model (SDM). The basic results show that the development of the digital economy in the social sphere positively influences the growth of GTFP, and there is a spatial spillover effect. Specifically, the 1% increase in social sphere digitalization will bring a 0.0705% increase in GTFP. Furthermore, influencing mechanisms of the digital economy on GTFP are exam-ined, namely industrial structure upgrading, human capital, and technological invention effects. Last, the het-erogeneity analyses show that the influencing intensity is different in Eastern, Middle, and Western cities as well as in resource-based and non-resource-based cities. Our findings provide new evidence for the relationship be-tween the social sphere digitalization and green development, and also give managerial implications for other cities or countries that are seeking energy and emission-reduction measures.2023-05-30T07:37:06ZEffect of cloud-based information systems on the agile development of industrial business process managementWang, JianXu, Yi-PengShe, Chenhttp://ir.casisd.cn:80/handle/190111/120522023-05-30T07:37:03Z2023-05-30T07:37:03Z题名: Effect of cloud-based information systems on the agile development of industrial business process management
作者: Wang, Jian; Xu, Yi-Peng; She, Chen
摘要: Business process management (BPM) has been the main driver behind company optimization and operational efficiency. However, the digitization era we live in necessitates that organizations be agile and adaptable. Delivering unprecedented rates of automation-fueled agility is necessary to be a part of this digital revolution. On the other hand, BPM automation cannot be done only by concentrating on procedure space and traditional planning methodologies. With the introduction of BPM, where the deployment of BPM with cloud computing has undergone enormous development lately, cloud computing has been considered a particularly active topic of study. Cloud computing points to the provision of dependable computing environments based on improved infrastructure availability and service quality without imposing a significant cost load. This research aims to discover the relationship between technical factors, financial factors, environmental factors, security of the cloud-based information systems, and the agile development of industrial BPM (IBPM). The present study aims to fill this gap and show how partial least squares structural equation modeling (SEM) can be employed in this field. Importance-performance map analysis (IPMA) evaluated the importance and performance of factors in the SEM. IPMA enables the identification of factors with relatively low performance but relatively high importance in shaping dependent variables. The empirical findings showed that four key factors (technical, financial, environmental, and security) positively influence the agile development of IBPM.2023-05-30T07:37:03ZThe functional evolution and system equilibrium of urban and rural territoriesFAN, JieLI, SisiSUN, ZhongruiGUO, RuiZHOU, KanCHEN, DongWU, Jianxionghttp://ir.casisd.cn:80/handle/190111/120492023-05-30T07:36:59Z2023-05-30T07:36:59Z题名: The functional evolution and system equilibrium of urban and rural territories
作者: FAN, Jie; LI, Sisi; SUN, Zhongrui; GUO, Rui; ZHOU, Kan; CHEN, Dong; WU, Jianxiong
摘要: The coordinated development of urban and rural territorial systems has long been a scientific issue of concern in geography and socioeconomic development in China. Based on Territorial Function Theory, this paper establishes a theoretical framework to support the coordinated development of urban and rural territorial systems, analyzes the trend of functional evolution, discusses the impact of efficient allocation and orderly element flow on system equivalence development, and puts forward approaches and policy suggestions for equilibrium development in the future. The main conclusions are as follows: (1) The evolution of urban and rural territorial functions has experienced four stages: rural to rural, rural to urban transition, rural to urban, and urban to urban. In this process, territorial functions have been developed to be hierarchical and advanced. (2) Functional evolution enables urban and rural comparative advantages to be transformed from value difference to value equivalence. Increasing the flow intensity and reconstructing the flow space have become the necessary conditions for the coordination of development. (3) Land is the most important resource in China, and land system reform is the key to achieving equivalence development of urban and rural territorial systems, thereby determining the future equilibrium development of the two systems.2023-05-30T07:36:59ZLeveraging multidimensional features for policy opinion sentiment predictionHou, WenjuLi, YingLiu, YijunLi, Qianqianhttp://ir.casisd.cn:80/handle/190111/120462023-05-30T07:36:55Z2023-05-30T07:36:55Z题名: Leveraging multidimensional features for policy opinion sentiment prediction
作者: Hou, Wenju; Li, Ying; Liu, Yijun; Li, Qianqian
摘要: Previous online policy opinion analyses based on social media data have focused on topic detection and sentiment classification of policy opinion after a given period following pol-icy implementation. These approaches are limited and inefficient because they provide no opportunity to change citizens' opinions once they have been formed. Furthermore, incor-porating auxiliary information to enrich semantic representations is vital and challenging due to limited texts, and a lack of both semantic information and strict syntactic structure. Therefore, we propose a novel framework to extract and integrate multidimensional fea-tures from user-related and policy-related social media information and predict policy comment polarity in the policy release phase. First, we construct four machine learning models for model-induced features to capture topic-related and opinion-related features and identify the policy-opinion nexus. In addition, we integrate basic and behavioral user features. Then, we leverage multidimensional features to construct a stacked learning model for predicting the policy opinion. Finally, we conduct experiments on 20 policy com-ment datasets to demonstrate that our prediction framework can effectively predict public opinion about a policy once it is released. Our model provides key insights into policy opin-ions in advance and can enable policymakers to engage in better policy communication before opinion formation. (c) 2022 Elsevier Inc. All rights reserved.2023-05-30T07:36:55Z